Vinay Kumar
New Delhi,DL
Summary
Data Analyst with over 4 years of experience in collecting, analyzing, and interpreting large datasets to drive successful business solutions. Proficient in advanced data modeling, and data visualization techniques. Expert in SQL, Python, and Excel,Power BI with a strong foundation in statistics and data science principles.
Overview
6
6
years of professional experience
1
1
Certification
Work History
Data Analyst
Teleperformance
Gurgaon, India
10.2021 - Current
- Developed and executed data cleanup measures
- Utilized data visualization techniques to present and explain complex data sets
- Analyzed data to identify root causes of problems and recommend corrective actions
- Developed SQL queries to obtain complex data from tables in on-site and remote databases.
Data Analyst
Interglobe Private LTD
Gurgaon, India
10.2020 - 10.2021
- Improved decision-making processes with accurate data analysis and visualization techniques.
- Used statistical methods to analyze data and generate useful business reports.
Jr. Data Analyst
Teleperformance
Gurgaon, India
06.2018 - 04.2020
- Increased efficiency in data extraction by utilizing SQL queries for retrieving relevant information from databases.
- Identified trends and patterns in complex datasets, translating findings into easily understandable visualizations and reports.
Education
B.Com -
Accounting Delhi University
07.2015
Skills
- My SQL
- Power BI
- Python
- NumPy
- Pandas
- SSIS (2016)
Certification
- Careerera - CERTIFICATE OF ACHIEVEMENT Post Graduate Program in Data Science
- Internship - SNVA LLC CERTIFICATE OF COMPLETION
- Simplilearn - Artificial intelligence engineer
Projects
Honda car price :-
Objective: Analyze and predict the factors influencing Honda car prices.
Methodology: Utilized Python for data analysis, statistical modeling, and data visualization.
Tools and Technologies: Python (Pandas, Scikit-learn), Matplotlib.
Key Findings: Identified critical factors such as model year, mileage, and location impacting car prices. Developed a predictive model with 90% accuracy.
Online Food Services Analysis Project
Objective: Analyze and optimize the delivery and marketing strategies for an online food delivery service.
Methodology: Data collection and analysis using Python, machine learning for predictive modeling, and data visualization with Tableau.
Tools and Technologies: Python, Scikit-learn, Tableau, SQL.
Key Findings: Identified key drivers of customer satisfaction and seasonal ordering trends. Developed a predictive model for customer retention with 85% accuracy
Timeline
Data Analyst
Teleperformance
10.2021 - Current
Data Analyst
Interglobe Private LTD
10.2020 - 10.2021
Jr. Data Analyst
Teleperformance
06.2018 - 04.2020
B.Com -
Accounting Delhi University